code: def __init__(
      self,
      n_loop,
      n_layer,
      a_channels,
      r_channels,
      s_channels,
      use_embed_tanh,
  ):
      super(WaveNet, self).__init__()
      with self.init_scope():
          self.embed = L.Convolution1D(
              a_channels, r_channels, 2, pad=1, nobias=True
          )
          self.resnet = ResidualNet(
              n_loop, n_layer, 2, r_channels, 2 * r_channels, s_channels
          )
          self.proj1 = L.Convolution1D(
              s_channels, s_channels, 1, nobias=True
          )
          self.proj2 = L.Convolution1D(
              s_channels, a_channels, 1, nobias=True
          )
      self.a_channels = a_channels
      self.s_channels = s_channels
      self.use_embed_tanh = use_embed_tanh
  
file_path: chainer/examples/wavenet/net.py
imports: import chainer
  import chainer.functions
  import chainer.links
  from modules import ResidualNet
label_desc: Use image node_id 1 to create a new WaveNet object from inherited base classes: chainer with example: obj = WaveNet(n_loop, n_layer, a_channels, r_channels, s_channels, use_embed_tanh)